My machine programming company's website: http://merly.ai
My Machine Programming & Technology YouTube Channel (subscribe & stay updated)
Keynote at LADSIOS (co-located with VLDB '21): "Machine Programming and the Future of Software Development"
New demo of one of our production quality MP systems: AutoPerf
Our team, joint w/ MIT & Microsoft, won two awards at SIGMOD '21!
Keynote @ MIT's DSAIL 2021 virtual retreat: "A Glimpse Into Machine Programming @ Intel Labs"
Keynote @ Penn's PRECISE 2019 Industry Day: "Machine Programming: The Future of Autonomy"
NeurIPS '22, ICLR'22, PLDI'22, CGO'21, NeurIPS'21, AIDB'21, PACT'21, FSE'21, OOPSLA'21, MAPS'21 (SC chair), ICML'21, USENIX ATC'21, ICLR'21, MLSys'21, NeurIPS'20, MAPL'20 (SC chair), JPDC'20, aiDM '20, TheWebConf'20, MLSys'20, PACT'19 (SRC), SysML'19, MAPL'18 (general chair)
Brief Biographical Sketch
In December 2021, I founded Merly, Inc., a Silicon Valley start-up that aims to disrupt software development. I am Merly's Chief Executive Officer (CEO) and Chief Scientist. Merly is principally interested in (i) improving the rate at which we develop software while concurrently (ii) improving its quality. We achieve this by employing a variety of automation techniques -- otherwise known as machine programming -- such as deep neural networks and formal methods. Learn more here (https://merly.ai)!
Previously, I founded and led the Machine Programming Research group at Intel Labs. Machine programming (MP) is a new field of research that uses automation to improve the rate at which we develop software (e.g., the time it takes a developer to write, maintain, and test code) and improve its associated quality characteristics (e.g., performance, correctness, security, maintainability, etc.). We generally consider MP as a fusion of machine learning and formal methods, which rely heavily on programming languages and systems. We provide a brief overview of MP in our “Three Pillars of Machine Programming” vision paper (see my Stanford MP course page or Armando Solar-Lezama's website for a deeper dive).
In academia, I am a lecturer at Stanford University, where I teach the "Machine Programming" graduate computer science course.
I have ~40 peer reviewed papers, ~70 issued patents, and ~130 patents pending. I've been lucky enough to have been invited to give talks at places like Berkeley, BMW, DARPA, IBM Research, MIT, Penn, Stanford, UCLA, University of Washington, VMWare, and Wharton, amongst others. I've had the tremendous honor to give keynote addresses at places like VLDB (LADSIOS), University of Pennsylvania, the US Department of Energy, and MIT. My team's research has been highlighted by venues like The Wall Street Journal, DeepLearning.ai, Communications of the ACM, MIT Technology Review, The New York Times, and many others.
Keynote address at LADSIOS (co-located with VLDB '21): "Machine Programming and the Future of Software Development"
[Milestone] 50th patent issued: "Methods and apparatus to detect side-channel attacks"
Our team, Machine Programming Research (MPR), won two awards at SIGMOD '21!
MS advisor (University of Pennsylvania): Brad MacDonald -> Tesla
MS co-advisor (University of Pennsylvania): Celine Lee -> Intel Labs, then PhD student @ Cornell
PhD committee member (Lehigh University): PanteA Zardoshti -> Microsoft Research
PhD committee member (University of Washington): Maaz Ahmad -> Adobe Research